lora_fine_tuned_cb

This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.4089
• Accuracy: 0.3182
• F1: 0.1536

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 400

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.9467	3.5714	50	1.1690	0.3182	0.1536
0.7755	7.1429	100	1.2983	0.3182	0.1536
0.7396	10.7143	150	1.3709	0.3182	0.1536
0.6894	14.2857	200	1.3939	0.3182	0.1536
0.7253	17.8571	250	1.4084	0.3182	0.1536
0.7187	21.4286	300	1.4133	0.3182	0.1536
0.6998	25.0	350	1.4096	0.3182	0.1536
0.7152	28.5714	400	1.4089	0.3182	0.1536

Framework versions

• PEFT 0.10.1.dev0
• Transformers 4.40.1
• Pytorch 2.3.0
• Datasets 2.19.0
• Tokenizers 0.19.1